Learn · updated 2026-10-23
Control chart constants: A2, D3, D4, d2, c4 and the rest
Control limits sit three standard deviations of the plotted statistic from the center line, but on an X̄-R or X̄-S chart you estimate the standard deviation from ranges or subgroup standard deviations. The constants turn those averages into limits, so you only multiply.
Which constant goes where. X̿ is the grand mean, R̄ the average range, s̄ the average subgroup standard deviation, n the subgroup size.
X̄-R chartX̄: X̿ ± A2 × R̄R: D3 × R̄ to D4 × R̄X̄-S chartX̄: X̿ ± A3 × s̄S: B3 × s̄ to B4 × s̄I-MR chart (moving ranges of 2)I: X̄ ± 2.66 × MR̄MR: 0 to 3.267 × MR̄Process σσ = R̄ / d2 or σ = s̄ / c4
The table
Subgroup sizes 2 to 25. Use the row for the number of parts in each subgroup.
For X̄-R charts (ranges)
| n | d2 | d3 | A2 | D3 | D4 |
|---|---|---|---|---|---|
| 2 | 1.128 | 0.853 | 1.880 | 0 | 3.267 |
| 3 | 1.693 | 0.888 | 1.023 | 0 | 2.575 |
| 4 | 2.059 | 0.880 | 0.729 | 0 | 2.282 |
| 5 | 2.326 | 0.864 | 0.577 | 0 | 2.114 |
| 6 | 2.534 | 0.848 | 0.483 | 0 | 2.004 |
| 7 | 2.704 | 0.833 | 0.419 | 0.076 | 1.924 |
| 8 | 2.847 | 0.820 | 0.373 | 0.136 | 1.864 |
| 9 | 2.970 | 0.808 | 0.337 | 0.184 | 1.816 |
| 10 | 3.078 | 0.797 | 0.308 | 0.223 | 1.777 |
| 11 | 3.173 | 0.787 | 0.285 | 0.256 | 1.744 |
| 12 | 3.258 | 0.778 | 0.266 | 0.283 | 1.717 |
| 13 | 3.336 | 0.770 | 0.249 | 0.307 | 1.693 |
| 14 | 3.407 | 0.763 | 0.235 | 0.328 | 1.672 |
| 15 | 3.472 | 0.756 | 0.223 | 0.347 | 1.653 |
| 16 | 3.532 | 0.750 | 0.212 | 0.363 | 1.637 |
| 17 | 3.588 | 0.744 | 0.203 | 0.378 | 1.622 |
| 18 | 3.640 | 0.739 | 0.194 | 0.391 | 1.609 |
| 19 | 3.689 | 0.733 | 0.187 | 0.404 | 1.596 |
| 20 | 3.735 | 0.729 | 0.180 | 0.415 | 1.585 |
| 21 | 3.778 | 0.724 | 0.173 | 0.425 | 1.575 |
| 22 | 3.819 | 0.720 | 0.167 | 0.435 | 1.565 |
| 23 | 3.858 | 0.716 | 0.162 | 0.443 | 1.557 |
| 24 | 3.895 | 0.712 | 0.157 | 0.452 | 1.548 |
| 25 | 3.931 | 0.708 | 0.153 | 0.459 | 1.541 |
For X̄-S charts (standard deviations)
| n | c4 | A3 | B3 | B4 |
|---|---|---|---|---|
| 2 | 0.7979 | 2.659 | 0 | 3.267 |
| 3 | 0.8862 | 1.954 | 0 | 2.568 |
| 4 | 0.9213 | 1.628 | 0 | 2.266 |
| 5 | 0.9400 | 1.427 | 0 | 2.089 |
| 6 | 0.9515 | 1.287 | 0.030 | 1.970 |
| 7 | 0.9594 | 1.182 | 0.118 | 1.882 |
| 8 | 0.9650 | 1.099 | 0.185 | 1.815 |
| 9 | 0.9693 | 1.032 | 0.239 | 1.761 |
| 10 | 0.9727 | 0.975 | 0.284 | 1.716 |
| 11 | 0.9754 | 0.927 | 0.321 | 1.679 |
| 12 | 0.9776 | 0.886 | 0.354 | 1.646 |
| 13 | 0.9794 | 0.850 | 0.382 | 1.618 |
| 14 | 0.9810 | 0.817 | 0.406 | 1.594 |
| 15 | 0.9823 | 0.789 | 0.428 | 1.572 |
| 16 | 0.9835 | 0.763 | 0.448 | 1.552 |
| 17 | 0.9845 | 0.739 | 0.466 | 1.534 |
| 18 | 0.9854 | 0.718 | 0.482 | 1.518 |
| 19 | 0.9862 | 0.698 | 0.497 | 1.503 |
| 20 | 0.9869 | 0.680 | 0.510 | 1.490 |
| 21 | 0.9876 | 0.663 | 0.523 | 1.477 |
| 22 | 0.9882 | 0.647 | 0.534 | 1.466 |
| 23 | 0.9887 | 0.633 | 0.545 | 1.455 |
| 24 | 0.9892 | 0.619 | 0.555 | 1.445 |
| 25 | 0.9896 | 0.606 | 0.565 | 1.435 |
Worked example
Say you measure 5 parts an hour and after 25 hours have X̿ = 10.00 mm and R̄ = 0.20 mm. From the n = 5 row:
- X̄ chart: 10.00 ± 0.577 × 0.20 → UCL 10.115, LCL 9.885.
- R chart: UCL = 2.114 × 0.20 = 0.423; LCL = 0 (D3 is 0 for n ≤ 6).
- Process σ = 0.20 / 2.326 = 0.0860 mm, the σ to use for Cp and Cpk.
The X̄-R chart guide works a full example with real subgroups.
Where they come from
- d2 is the average range of n values from a normal distribution with σ = 1, so σ ≈ R̄ / d2. d3 is the standard deviation of that range.
- c4 corrects the subgroup standard deviation, which runs a little low on average: σ ≈ s̄ / c4. It is √(2/(n−1)) × Γ(n/2) / Γ((n−1)/2).
- A2 = 3 / (d2 √n): three standard errors of a subgroup mean, in units of R̄. A3 = 3 / (c4 √n), the same in units of s̄.
- D3, D4 = 1 ∓ 3 d3 / d2, and B3, B4 = 1 ∓ 3 √(1 − c4²) / c4. A negative lower value is set to 0, which is why small subgroups have a lower limit of 0 on the R or S chart.
- 2.66 on the I-MR chart is 3 / d2 for n = 2 (3 / 1.128), and 3.267 is D4 for n = 2.
R or S?
The range throws away the values between the largest and smallest, which costs little with small subgroups and more as they grow. NIST puts the range's efficiency at 0.955 for n = 5 and 0.850 for n = 10. Use X̄-R up to about 9 parts per subgroup and X̄-S from 10.